6 papers
AutoAdapt: Reliable Few-Shot Adaptation under Clinical Distribution Shifts
Song Wang, Jie Peng, Davis Hobley +2
Large pretrained clinical models provide a practical way to reuse learned prior knowledge across hospitals by adapting models to them. In practice, a target hospital may only have…
Sign-Constrained Intervention Effects for Domain-Generalizable ICU World Models
Zhen Xu, Nicholas Konz, Zhen Tan +2
Predicting how a patient's vital signs respond to an intervention is a central question in intensive care. World models can do so by learning dynamics as a function of prior action…
Aligning Multimodal Patient Evidence with Biomedical Knowledge Graphs for Clinical LLMs
Jiawen Du, Arshan Ali Khan, Chenhao Zhang +7
Clinical questions often depend on linking a patient's multimodal evidence to external biomedical knowledge, yet existing predictive systems rarely represent such links explicitly,…
Training and Scaling Compute-Optimal Physiological Waveform Foundation Models
Pingzhi Li, Jie Peng, Shuqing Luo +2
We investigate the scaling laws and compute-optimal training of physiological waveform foundation models (FMs). We train Aether, a family of over one hundred FMs ranging from 20M t…
On the Divergence of Accuracy and Mechanism Consistency in Time Series World Models
Haochen Zhang, Jiaheng Guo, Zhen Xu +4
A time series world model (TSWM) predicts a controlled system's state from its observed history and planned actions and exogenous inputs. Current approaches build forecasters with…
LineupRL: Verifiable Reinforcement Learning for Time Series Captioning via Caption-to-Series Identification
Haochen Zhang, Laura Yao, Zachary Plotkin +2
Time series captioning is a fundamental step in time series understanding and can also serve as the bridge between signal and natural language. Supervised fine-tuning (SFT) relies…